Category: sensor network


The applications built on wireless sensor networks are becoming increasingly attractive for monitoring and control applications in various domains such as smart building, home automation, smart transportation.  However due to characteristic of heterogeneous wireless network in terms of wireless network standards and application protocols, actuation in wireless sensor networks are still largely confined in isolated and constrained intranets, increases more complexities as the heterogeneous wireless networks grow bigger.  While standing in contrast to the concentrating the application logic on the sensing level,  solutions based on IP web will provide convergence for heterogeneous wireless networks, and more semantic interoperability in time and location, facilitating monitoring, control and automation. And furthermore authentication with both user and devices’s access to the web becomes even more significant in security concern. I will present the concept and web service architecture of our semantic sensor web by complying with multiple wireless sensor network standard and sensor web standard.


Internet of things, which is the vision of a world where all electronic devices are connected together to form a single, coherent network of heterogeneous devices, is rapidly approaching to a reality, reshaping our world by collecting, processing, analysing huge amounts of real-time data produced from the physical world, thereby notifying users or actuating the devices according to application logic and domain contexts.

Over a long time, large volumes of environmental and personal health information created naturally through our surrounding physical world has been lost or confined in small scale constrained network environments. That is how wireless sensor networks comes to play, connecting a large set of wireless low cost, small size,low power nodes to sense all various of environmental factors such as temperature, humidity, imminence in our physical space. However merely putting application logic on the wireless sensor networks leads to many limitations and weakness.

First of all, the mote is generally resource constrained environments in terms of power,computation capacity and memory, putting application logic takes much space of resource. Booting and updating the software in that environment is also becoming a complex issue. Moreover the implementation of commercial WSN involves, in many case, wireless sensor standards,  and moreover proprietary application programming interfaces and protocol. The use of different proprietary data formats and protocols constitutes a bottleneck for the expansion of these networks, especially on the actuation. In general,  the price of converting different protocols gets higher as more heterogeneous networks are getting involved on the sensing level. For example, Zigbee and 6lowpan are both wireless sensor standards both adopting 802.14 standard who defines the Physical layer and Mac layer, but differs on the networking layer and application layer.


This should give you a idea of how this could look like!

Therefore shifting the control from resource constrained environment to the IP based web gains enormous advantages over the disadvantages. First of all, with the existing robust Internet infrastructure in terms of standards, scalability, security, web can provide a more powerful environment in the storage, computation, and analysing , concurrently executing process, analysis, which in most circumstances are complex application logic, and invoking the notification and actuation simultaneously on the web service level. Various wireless network applications can be built on top of web instead wrapping the logic inside resource-constrained environment,  the radio-specific wireless network like zigbee should be less about processing application logic, but more on transporting the information. Historically, a network is likely to be more successful if the majority of its logic is pushed to the edges.
Moreover, web addresses the limitations of heterogeneous wireless networks by hiding the underlying layers, the network communication details, and heterogeneous sensor hardware.  In that sense, web offers the convergence of heterogeneous wireless networks through IP standards.

And the emerging concept of semantic web allows semantic information such as location, time to be added to  the sensor data, making raw sensor data meaningful to the web applications and naive users.. Semantic sensor web helps naive user to discover, access and search sensor data on the Web, building context – awareness applications.

Lastly, billions of users has been and will continue relying on the web for growing and reliable information. Obviously over years, web has evolved to be a inter-connecting platform that allow billions of users contributing, sharing, socializing, various applications and services are built upon it, serving the purpose of bridging the user and our digital world. Likewise, thought the web ecosystem, users can get access to exploding amounts of device-generated content in the similar experience, And this time, web serves as mediator building the gap between users and wireless network environment, the long term divide between virtual world and physical world is about to set change.

In going forwards from heterogeneous wireless network to semantic sensor web, several critical issues should be further discussed, including wireless sensor network standards, sensor meta data, sensor web ontology, a uniform solution of semantic sensor web is going to combine 3 of them for the further actuation and monitoring applications. While pushing the application logic to the web for monitoring or significantly controlling and automation, security becomes a critical issue that nobody wants his device to be maliciously accessed or controlled by people who have no authentication. Therefore authentication on the web for user getting access to his device is a pressing emphasis particularly.


The pros of zigbee is about its application profile agreed on by vendors, therefore the command identifiers and attributes defined in the public application profile work smoothly though the overall zigbee sensor network .

The cons of zigbee is mixing application logic with networking security methnizthm, and works slowly on its compatiability with IP6.


source :

The transcript of my talk at LIFT this afternoon. Thought it would be a good intro to WoT (although very high level), so I shared it here. Thoughts & feedback more than welcome! Yeah, it’s a lot of text, and it’s ugly to read on a blog, so I also made a pretty PDF you can print or read later.

As a PhD student at ETH Zurich and SAP, I have been exploring the Internet of Things (IoT), which is the vision of a world where all electronic devices are connected together to form a single, coherent network of heterogeneous devices. In theory, such a large network could collect real-time data from the physical world that can be used to solve all our problems, improve traffic in large cities, reduce pollution and energy consumption, take better care of the elderly and so on.

All this sounds nice in theory, but the reality is unfortunately different.

Early in my research, I realized that the Internet of Things is merely a scam – it is a leaky concept. On the one hand we have academic research that is not really concerned with standardization issues, therefore many incompatible solutions/projects have been explored by diverse research groups pretty much in isolation. On the other hand, we have the industry which is very interested by standards, as many companies that want to lead the IOT, so hundreds of protocols to communicate with devices have been created, proposed, even standardized. But are these standards really used? I mean by more than a few thousands IT experts in a very specific domain?

standardization is always a big issue, going beyond the standard is not possible, therefore choosing a right standard is much significant


Let me illustrate this with a small sample of such standards commonly used in home automation and machine-to-machine communication. How many of you know and can develop using one of these protocols? Humm… yeah… This is exactly what I mean by leaky concept. Such a messy world where all of these protocols – or non-standard standards as I like to call them – co-habit, cannot become a unique Internet of Things. The reality today is that we have built many Intranets of things. Yes they work and do the job, but they remain isolated islands of a few connected devices. These islands have practically no way to interact with each other, and this observation reduces the classic vision of Internet of Things to merely an utopia. The status quo, makes it hard to share and reuse solutions, as for each new deployment tons of things need to be developed over again from scratch.

Obviously many underlying wireless network protocols, makeup launage, web standard will co-exist for a long time.

Connecting the heterogeneous and isolated intranets seems quite challenging, yet IP convergence is no doubt the best solution bridging the gaps of various heterogeneous wireless networks.

If we think another way around,  web based on IP protocol, the most successful invention of human kind,  is already paving the way for future applications and heterogeneous networks since it is the open, easy , scalable experimenting platform  for everyone.

it, also bridges sensing level (wireless sensor network) and mobile application level (mobile internet).

Reuse the existing mature web expertise, protocol, standard, tool is one big reason.

Some reason of reuse of web is by working on its massive open data with more advanced artificial intelligence techniques, it facilitates the further understanding of how our world functions in depth

This is a huge waste of time and resources.

In fact, there is already a single standard out there to bind them all. We all know it and use it everyday: the Web.

It is efficient and works well, and the reason the Web has become so successful is because it was free, open, flexible, and designed to be massively scalable. But above all, the main reason it has worked is because it was so simple, open, free, so anyone could use it. You became part of the Web by designing your first Web page using Frontpage and cheesy animated GIFs. Anyone could be part of it. All you needed was a computer, a modem and a text editor. This aspect is so fundamental that with my colleague Dom, we have explored how to adapt this magic recipe for electronic devices. They have a right to be part of the Web too, and as I will explain in this talk there are many reasons why they should be. Beyond obvious business opportunities by web-enabling devices, we have accumulated two decades of knowledge in building massively scalable, secure, and efficient Web sites. We have built a wealth of expertise for distributed caches, replicative DBs and so on. Why not reuse all that for devices too? Why do we need to reinvent wheels?


My argument here is that there is not a single world wide web, but 5 of them. We can see them as various trends, or facets of the Web as we know it today, and we all know and understand them. But, at the intersection of these 5W, when all these pieces are put together, a whole new, unknown territory emerges, and brand new possibilities to solve old problems are unlocked. This design space there is what we call the Web of Things. But first, let’s first focus a little more on the physical Web and programmable Web.

Once upon a time, electronics and programming was reserved to the highest social class of our civilization, geeks. However, one day processing and Arduino appeared. This explosive cocktail has revealed to the world the conspiracy nerds were setting up, by demystifying our virtues and showed to the world how easy it actually is to program. Since then, countless designers and other people who were not meant to touch technology were suddenly empowered to create digital artifacts easily, on their own.These tools are an incredible example of how simple tools can democratize programming, by lowering the barrier for fast prototyping physico-digital artifacts.

openness spreads from the web to the device, invoking a further evolution of internet of things

How many of you can program processing/arduino?Not enough.

We want more people to be able to access and use real-time data. Not just raw sensor readings. I’m talking about data people care about. Data that can make our lives easier. Data that could make us happier. We believe the Web of Things to be the next evolution of the Web by enabling the democratization of programming and active citizenship. We believe this because the Web offers the lowest possible access barrier to simply create something that you can share with the world. Now how many of you have already made a Web page? Or setup a blog? Get my point? Everyone is a potential developer for the Web of Things. And you will be able to access and integrate real-time data from all kinds of sensors, simply by pasting someHTML code on your web page.

reuse and put the web 2.0 concept into internet of things

I would like to share the vision of a large ecosystem of ubiquitous digital services roaming around, freely accessible. Imagine an ecosystem of reusable and shareable sensors, devices, and services that can be accessed simply via a Web API, using simply your facebook login information. Just by sending HTTP POST/GET request to a device, you read a sensor, you open a door. There are two ways to interact with this ecosystem: 1) “READ”: collect data they record automatically and analyze it, or 2) “WRITE”: pop up your phone, browse the space you’re in for example query for an empty restaurant, call a cab, turn on lights, music or AC.


Let’s start directly the WRITE aspect first through an example. Imagine you go to a hotel in Japan, it’s freezing and you’re handed a remote like this. Chances are the accompanying translation such as this one is not included. What do you do? Why can’t you just pop out your phone and control the AC directly with it? Or setup your alarm or book a tennis course offered by the hotel? Or even better, discretely ordering some champagne and caviar for your lady and play some romantic music while dimming the light? In a hotel room in Japan you’ve never been!!


Now… what if I told you that for less than 10 dollars, you can buy a simple chip with a Wi-Fi antenna that could turn anything into a Web server? This means, any electronic thing can be connected to the Web and can be controlled via a Web API, and you would literally browse around the “physical” page of your room and find about the things in the physical world you could control? And just like most Websites in the world, it would recognize the language your phone and give you the room page in this same language.

Niwea is a term coined out by my friend hannes gassert, and stands for Native Interoperable WEb Apps (I wrote a bigger post about this earlier). If you’re in the software industry, chances are a client or your boss told you “we need an iphone/symbian/windows mobile/android app”. Of course, many self-respecting developers might reply “no, you don’t really. You can do this apponly need a simple HTML/Javascript app that uses CSS style sheets to render your applications on these diverse mobile phones”. So you only develop once a Web app, and it’ll run on many devices. After this simple suggestion, the contra-argument generally goes along the lines of “bla bla want iphone app bla bla!!”. Sencha, jQTouch, iui are some of those frameworks. They are not great yet, but it’s only the beginning. Think about it: how many of you have made an iPhone app? Should I ask again about Web apps? iPhone developers: few and expensive (won’t even mention code maintenance), Web developers: cheap & easy (and we got lots of ‘em).

If you need performance or support for the native platform (GPS, camera, audio, etc), the N of niwea kicks in. Using phonegap, you can transform your Web app into a real, native app that will look, feel, and work just like the real thing. Only that it took you a few hours and $$ to make.

I do believe many more frameworks for fast prototyping Web apps (especially mobile) will appear and mature in the next years. Hopefully, more complete IDEs such as Flash) for developing interactive mobile Web apps with a few clicks. There is so much potential there!


Now let’s look at the other interaction mode, the “READ” aspect. O’Reilly has just organizedSTRATA, a conference that looks into data science – that is how to address this big question: how to efficiently analyze tons of raw data to extract meaningful information that could improve business process, marketing, etc.

But what if the data in question is physical data? I spent the last couple of months exploring this possibility with the Senseable City Lab at MIT, on a project called LIVE Singapore! Let’s take a city, for example Singapore. Lot of digital data traces are generated there every second via cameras, sensors of all kinds, radars & electronic road pricing, people with mobile phones, etc.


All this data represents a goldmine for everyone, if only it were to be used. Unfortunately, different companies collect it only to ensure everything works fine, and that’s it. It’s then stored behind closed doors – or worse, deleted – but rarely thoroughly analyzed. If only one could access it, so much valuable information could be extracted from it – valuable both for the company who could improve their processes or optimize their operations and citizens at large.

Optimizing water used to irrigate parks, managing the lighting in a smart way, providing an information system of free parking spaces or water leaks in pipes are problems common to most cities: they all could be treated with an intelligent monitoring system that would help in the daily management of resources.

There is a lot of information there that could be used to build a more efficient city, and using new technologies to collect this data represents a massive potential to build more efficient cities. In the LS project we are building a massively scalable platform that allows to collect hundreds of streams of raw data from various agencies in real-time and process all that to infer higher-level information that can be dispatched to various agencies to optimize joint efforts.

I do believe a company that is very active in this area is IBM, via their Smarter Planet initiative. I am not affiliated to IBM and the ideas I express here are only mine. But they are a great case study because they are a global company that embrace the internet of things not just as a gadget or research topic, but as a concrete product that can solve major challenges our civilization faces. Recently they partnered with the city of Rio de Janeiro to build a new operations center that operates independently of any agency while receiving data from several of them, running it through a battery of algorithms to monitor, predict, and visualize vital information in real-time to decide how best to respond, and answer optimally things such as:“Which streets will require the most troops? Which hills are most prone to mud slides? Are there shelters that have vacancies? Which hospitals have beds available? What is the best way to exit from a soccer match at the Maracana? How should officials direct traffic coming from the Copacabana Beach? Where are police cars, emergency, ambulances? Where they should go?”


Drinking water is an increasingly valuable resource throughout the world, and as cities get bigger, efficiently distributing water is becoming a major issue. Current infrastructure is aging, pipe failures are fairly common (leaks, bursts) and various reports show that on average 30% of drinkable water is lost during transmission, the system operation and management itself is often inefficient, water can be contaminated biologically or chemically. These problems have tremendous effects! First, financially it’s a lot of investments and profits that go down the drain… literally. Besides, an exploding pipe in downtown costs lots of money to repair and degrades public image. Finally – and most importantly – it is a major public health concern, as in case of water shortage the energy costs to keep up with water demand will explode. Today, we know what comes in and what comes out, but the spatial and temporal resolution of data collected within the system is very low: we just know there’s a leak but we don’t know where and when exactly it happened.

New water management strategies and technologies are a major challenge we need to address, and the sooner the better. This is another project my colleagues from CENSAM are working on in Singapore. Called Waterwise, this project aims to monitor continuously the drinking water distribution systems using sensors distributed throughout the water distribution system. Connected via a 3G connection, they are able to monitor in almost real-time the various conditions inside the pipe system such as pressure temperature, and analyze the chemical and biological composition to detect abnormalities. Firstly, the ability to quickly detect, localize leak/burst, and react quickly can reduce the amount of water lost through leakage, reduce customer disruption and minimize the extent of pipe repairs. Secondly, on-line hydraulic modeling and calibration of a water system gives an accurate, up-to-date picture of the hydraulic state of a system (flow and pressure) and the estimated consumption/demand patterns within a water distribution system.


Some people might still wonder “Ok great, but can I actually make money with this WoT thingie”? The answer is yes, and tons of it. A use case we have worked on while at SAP was how to build much more flexible BI application that tap the power and flexibility of the Web. There are many important bits of information in an RFID-based supply chain, the 5W (what, when, where, who, which), and we need to integrate them efficiently and in real-time in other operations.

  • The “what”: what tagged products (EPCs) were read.
  • The “when”: at what time were the products read.
  • The “where”: where were the products read, in terms of Business Location (e.g. “Floor B”).
  • The “who”: what readers (Read Point) recorded this trace.
  • The “which”: what was the business context (Business Step) recording the trace (e.g. “Shipping”).

The EPCIS network (stands for Electronic Product Code Information System) is a set of tools and standards for tracking and sharing RFID-tagged products. It is there and used by many companies, and built by many global vendors such as SAP, oracle, IBM sell, or even the open source implementation, called Fosstrack. However, much of this data remains in closed networks and is hard to integrate. Obviously the existing products are pretty expensive and not for the average consumer.


Dominique has been exploring how to make it easier to use all this data, to integrate it into various applications, and especially how to build more flexible, scalable, global application for better logistics. We create an EPC appliance in the cloud (Amazon EC2) and we we build WebAPIs for accessing every standard in the cloud. With this, one can create:
1) a scalable, distributed DB for the RFID events (readings),
2) Business intelligence widgets using the EPCIS REST API,
3) Mobile Web Apps that can be used to monitor readers in-situ (HTML5 push for the actual implementation),
4) RFID / Sensors / Business apps (e.g., ERP) Web mashups (even people can do that, e.g., what to do when an object gets stolen?)


Over the years, we have received much criticism about building such an Orwellian society where everything is interconnected, tagged, tracked, monitored. I can’t deny these fears are justified, but just like with any other technology it’s not good or bad. It’s essential to put in the place not only the technical, but also legal barriers to minimize misuse of all this data. So let me ask you something: Are your e-banking transactions publicly available over the web? no. Are your emails publicly available online? No, unless you hit the notorious “reply all” button. Can I access your company’s intranet? Of course not.

We have been building sufficiently secure websites for almost two decades, and in the Web of Things, these well-known mechanisms would come for free. I’m not insinuating these are perfect, but that they are good enough for most use cases. So why not just leverage them for physical devices?

  1. WoT is here and it matters, but it is not the best solution for everything.
  2. Think about niwea when you think mobile
  3. Stop talking, start prototyping

I hope that I’ve been able to explain what is the Web of Things, why is it different from the Internet of Things, and in what this difference matters. Hopefully, as more people understand the value and potential of sharing data for not only themselves, but for all of us, we’ll see more such projects emerge. This in turn will accelerate innovation and allow us to build more efficient and sustainable cities, without sacrificing the quality of life.

We would like to thank once more here all the people who helped and supported us (financially and psychologically) throughout our research. Of course our professor Friedemann Mattern and our colleagues and students at the distributed systems group at ETHZurich. Then SAP research and the EU projects socrades and sensei that have funded half of our phd. Then you all, the community that inspired us and reminded us that what we do actually matters, you’re all great!

Individual ‘s sense and perceptions of our surrounding world comes from the visual of eye, the hearing of ear, the feel and touch of skin, all of them are telling the information to our brains about what is going on right there. Look how wonderful gifts  that the god has given to all living creatures in the world, from which we  learn how to deal with our world, we can tell the good from bad,  know the danger and risk  in time, do and not do…

we can say, human is standing out in this world, surviving and evolving  for tens of thousands years, that has reached  a point of balance between ourselves and our nature world,  by functioning with these bunch of sensors to receive information, processing them with brain to make decision,   speaking them out with mouths or handwriting to deliver them to the rest of our peers…

we human are acting in this pattern like always, with sensing, processing, and networking. Apparently in most circumstances,  we are inferior in many ways compared with other creatures, not  sharp eyes like eagle, not acute ears like dolphin, not sensitive nose like dog. However, why human are considered to be a higher level creature is largely because that we bring all three things together in a perfect manner, convergence.

Human is evolving, so is the rapid changing nature world and human world accordingly. We are not very optimistic about the current situation of this world we are living in, with growing population, declining nature resources, degrading environment and various social problems caused by these. All things are pressing us, each one to think seriously, to move forwards, come up with solutions.

A solution with a better world we envision, what it could be, countless answers, but the question is how to bring it about, how can we proceed to fulfill that.

It is the point to do that, with the ability to combine the existing capabilities together,  sensing that gathers data in all corners of world,  networking that transforms and stores the information, artificial intelligence processes information automatically, mobile that gives the visibility of every changes of world that we concerns..

Convergence is starting in a large scale in between human society and nature world, equally like human body

sensor networking, sensor web,  semantic web , mobile web

More and more to be continued..

Who will make the race in low power wireless standards?

  • ZigBee?
  • 6LoWPAN?
  • Ieee 1451.5

Wireless sensor network & standards

Wireless Sensor Networks (WSN) are spatially distributed, autonomous sensors that cooperatively
monitor environmental conditions with application in military and civil domains (nature
and species monitoring, agriculture, production and delivery, health care, etc.) . WSNs are
highly dynamic and transient in their nature – connectivity is often unpredictable, devices disappear
and reappear changing network addresses, new ones are added to extend the network
or replace failed ones. They often include an abstraction layer for communication mechanisms
with a wide variety of sensor devices.

Several standards are currently either ratified or under development for wireless sensor networks. There are a number of standardization bodies in the field of WSNs. The IEEE focuses on the physical and MAC layers, defining 802.15.4 standard for low rate, low power wireless sensor network; the Internet Engineering Task Force works on layers 3 and above, introducing 6lowpan for integrating networks built over IP6,  alternatively ZIGBEE alliance also adopts 802.15.4, working on networking layer and application layer.

IEEE 802.15.4

IEEE standard 802.15.4 intends to offer the fundamental lower network layers of a type of wireless personal area network (WPAN) which focuses on low-cost, low-speed ubiquitous communication between devices (in contrast with other, more end user-oriented approaches, such as Wi-Fi), lower power consumption, large scale.It addresses the lower protocol layers (physical and MAC).


ZigBee is a open specification suit for for low-power wireless mesh networking of monitoring and control devices. It works in cooperation with IEEE 802.15.4. ZigBee 2007 defines the upper layers of the protocol stack, from the Zigbee Network Layer (NWK) to the Zigbee Application Layer, including application profiles to be followed by developers whenever they build devices.Each application profile has a unique profile identifier. The purpose of a profile is to create an interoperable, distributed application layer for separate devices. Profiles are simply standard rules and regulations.

One primary weakness of ZIGBEE stack is not interoperable with IP protocol, which limits its connections to other board range of IP – enabled devices and web services. Yet, this is about to change when ZIGBEE IP standards, along with Smart Energy Profile 2.0 come into public use soon. The new standard is closely in cooperation with several standard groups, such as IETF, W3C,IPSO, adopting 6LowPan, IP6, EXI as standards.


The IETF 6LoWPAN working group target was to define how to carry IP-based communication over IEEE 802.15.4 links in a manner to conform to open standards and to provide interoperability with other IP links and devices. In this way,  6lowpan is essentially a IP based wireless sensor network,consists of an Adaptation Layer, that allows IEEE 802.15.4 frames to carry IPv6 on top of it, then work in compatibility with UDP or ICMP transport protocols, With its transparency in Internet integration and flexible features like IP6 fragmentation and mesh forwarding, different companies can easily integrate LowPAN – devices into existing IP-structures, thus eliminating the need for an array of complex gateways.

What the 2 protocols share in common is that they are both based on IEEE 802.15.4 standard, both benefit from built-in AES128 encryption. Other than this, they are different in terms of networking layer and application layers.Interoperability is one of the leading factors when choosing a wireless protocol, essentially what makes them different is IP interoperability.

Current Zigbee stack doesn’t comply with IP, but takes many concepts and replaces much of the IP layer. For example, the Zigbee NWK layer is analogous to the IP layer, the NWK routing protocol, AODV, is analogous to IP’s RIP or OSPF, and the Zigbee Application Framework is analogous to the TCP layer (without the TCP state machine and the weird sequence space thing). Zigbee has endpoints, TCP has ports. Zigbee has endpoint grouping, TCP has port binding. The price of not being interoperable with IP is that bridging between ZigBee and non-ZigBee networks requires a more complex application layer gateway.

6LoWPAN offers interoperability with other wireless 802.15.4 devices as well as with devices on any other IP network link (e.g., Ethernet or WiFi) with a simple bridge device. More than that, it enables the use of a broad body of existing standards as well as higher level protocols, software, and tools. Concerning the code size, full featured stack of ZIGBEE is 90 KB, much larger than that of 6LoWPan, which is about  30 KB.

6LoWPAN is pretty attractive, since it is IP-based—the standard Internet working protocol. Yet, with strong ventor ‘s support on various application profile,  ZigBee is now shifting its focus, and start to converge to IP based – architecture including 6LowPan, IP6.  In that sense, new emerging Zigbee IP standard will continue to lead.




as for me, 6LoWPAN seems to very promising, in particular because it allows you to directly address a sensor node using IPv6.

Ieee 1451.5 is the solution combines the above 2, still on the working, it could be a great solution if accepted by the industry like Ieee 1451.2 or its peers. Yet, zigbee and 6lowPan are coming to convergence of IP, is there still a need of IEEE 1451.5

Native IP support has brought billions PC, mobile phone into the web, IP4  in this week has already come to a depletion, IP6 is rushing to us, to be a best and uniform choice and opportunity, so will ultimately benefit the sensor network.

Maybe in next 2 years IP6 will be more available enough bridging the gaps between sensor network and web, more importantly sensor web, with every wireless node would become part of the Internet!  zigbee standardlization so far is still a promising option in sensor network standared since its open application profiles in various domains, giving out a agreement among the vendors and developers.

hate translation, no gateway, zigbee+gateway type complex solutions seem unecessary when there is a direct IPV6 route you could take

although still waiting to see the performance of integration with zigbee and ip6,  hopefully coming soon

sensor network (zigbee or 6lowpan ) +  sensor makeup (sensorML)  + restful service (CoAP) + sensor ontology  =  semantic sensor web ???

sensorML too complex?  maybe with the help of exi, this problem could be eased ..


Fruit flies have solved a computing problem that has vexed computer scientists for decades.

Mimicking how some nerve cells in flies pick a leader to make decisions has led scientists to a computer algorithm that could make wireless sensor networks, such as those used for monitoring volcanic activity or controlling swarms of robots, much more efficient.

Usage: make wirelesss sensor network much more efficient in monitoring or controlling

In such smart networks, some sensors can act as leaders to alert headquarters if, for example, a certain number of them detect rumblings indicating that a volcano might be waking up. The new approach, published in the Jan. 13 Science, achieves the same leader-follower relationships but eliminates a lot of cross-talk among sensors, saving energy and computing power.

Scientists have copied the way some nerve cells in fruit flies pick a leader to help form a computer algorithm. The algorithm could help make wireless sensor networks. The new approach could be used for monitoring volcanic activity or controlling robot swarms.

A colleague’s presentation on how nerve cells in fruit flies take on different jobs struck computational biologist Ziv Bar-Joseph as being very similar to a distributed computing problem. In distributed computing, many computer processors work together toward a common goal, but with minimal leadership. A handful of processors — typically ones with many neighboring processors — are designated leaders and set up to receive information from the processors around them and pass it on.

“People in computer science made assumptions about what sensors need to know,” says Bar-Joseph, a researcher at Carnegie Mellon University in Pittsburgh who led the new work. But developing cells set up their networks without knowing much about their neighbors, he says. “They work in a much more constrained environment and still come up with solutions.”

  Problem: In smart sensor network, all smart sensors should work  in the simliar way like distributed computing, where a small handlful nodes are becoming the role of leader, coordinating the rest of nodes during the  ommunication process. However, due to its  constrained capability in power and memory, how could these leader node set up without knowing about their neighbors

Similarly, when fruit fly larvae are developing, some cells take on particular tasks, such as becoming a precursor of the sensory bristles the flies use to read the air around them. Each bristle ends up surrounded by nonbristle cells. This layout, where there are enough specialized cells, or leaders, but no two are right next to each other, is very similar to how tasks are divvied up in distributed networks, says Bar-Joseph.

For 30 years, computer scientists had thought that to most efficiently designate a handful of processors as leaders that can quickly communicate with the rest of the network, each processor had to take stock of its local neighborhood. Then some processors would identify themselves as leaders, based in part on how many connections they have with other processors.

Traditionaly, the leader node would identify himself as leaders, based on how many connections they have with other nodes

Young fruit fly nerve cells don’t necessarily know how many cells are in their neighborhood, yet they manage to develop into appropriately distributed sensory bristles. Once a cell elects itself as a bristle, it sends out a protein signal that inhibits neighboring cells from becoming bristles.

The flies’ trick lies in using timing instead of a neighborhood census to determine which cell becomes a bristle, Bar-Joseph and his colleagues report. As time passes, if a cell hasn’t received a don’t-become-a-bristle directive, it becomes a bristle, as simple as that. The new algorithm shows that networks of sensors could do the same, without spending time and energy gathering all that information on how many sensors are nearby, says Bar-Joseph.

The new trick lies in using timing instead of a neighborhood census to determine which cell becomes a bristle. As time passes, if a cell hasn’t received a don’t-become-a-bristle directive, it becomes a bristle,

“Now you don’t need to know about the neighborhood,” says Bar-Joseph. “Each sensor can be close to five or 500 sensors and it doesn’t need to know anything.”

The approach is “a delight” says Mark Fricker of the University of Oxford in England who is using slime mold behavior to build more efficient networks. “They have taken a very well-established biological developmental system and shown that it can be recast in a computational framework to solve an existing problem efficiently and effectively.”

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